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Technical Lecture

Device and Component Modeling

T38.4 - PiezoNet and Data-Driven Models for Time-Domain Characterization of Piezoelectric Resonators

Thursday, March 20, 2025
11:10 AM – 11:30 AM ET
Location: Level Three, A313
This paper presents a fully automated data acquisition platform and resulting database -- PiezoNet -- for data-driven characterization of piezoelectric resonators used in power electronics. The platform measures the voltage and the current over piezoelectric resonators across a wide range of excitation waveforms and ambient temperature. The power stage dynamically adjusts to efficient operating points for best operation under different load conditions. This system is mechanically versatile, accommodating crystals of diverse materials and dimensions. The platform enables comprehensive and precise characterization by automating the data collection process, thereby providing extensive datasets essential for training data-driven models (e.g., neural networks) to predict operating points and nonlinear behaviors. A family of sequence-to-sequence neural network models was trained and tested to validate the feasibility of data-driven models for piezoelectric resonators.